Research Engineer Robotics (Systems)

About the role

Reality Labs Research (RL-R) brings together a diverse and highly interdisciplinary team of researchers and engineers to create the future of dexterous robotic manipulation. We are seeking a staff Research Engineer with deep expertise in software engineering, robotic systems integration, and machine learning.

Responsibilities

• Architect & Own Real-Time Robotic Systems: Design and maintain real-time dexterous manipulation pipelines that integrate perception, planning, and control across multiple robotic platforms.
• Drive architectural decisions that enable rapid research iteration at scale
• Lead Data Capture & Retargeting Infrastructure: Architect motion capture integration, novel hardware prototypes, and human demonstration data collection systems.
• Build scalable processing pipelines for large multimodal datasets that enable efficient model training and real2sim transfer
• Drive ML-Systems Integration: Deploy and iterate on learned control policies (imitation learning, MPC, reinforcement learning) within full robotic systems.
• Partner with research teams to bridge the gap between algorithmic advances and real-world system performance
• Optimize Performance & System Reliability: Own runtime performance, debug complex system behaviors across the stack, and develop interactive demos and benchmarks that demonstrate research progress
• Set Technical Direction: Identify and drive cross-cutting technical improvements.
• Influence roadmap and priorities through deep system understanding and proactive problem identification
• Collaborate & Mentor Cross-Functionally: Work with diverse research and engineering teams to refine modules, drive end-to-end system improvements, and elevate the technical capabilities of the broader team

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 5+ years of experience in robotics engineering, including hands-on work with robotic platforms in industry or academic research settings
• Demonstrated experience with machine learning systems in a robotics context (e.g., learned control policies, perception models, or ML-driven planning)
• Full-stack systems engineering experience designing, building, and maintaining large-scale software-hardware systems
• Track record of driving complex, ambiguous technical projects from conception through delivery with minimal direction
• Experience communicating technical decisions and system designs to cross-functional stakeholders across research and engineering functions (e.g., design documents, technical reviews, project proposals)

Preferred Qualifications

• Experience building and operating systems that bridge research exploration and reliable deployment
• Background in computer vision, imitation learning, reinforcement learning, model-predictive control, or sim-to-real transfer
• Master's or Ph.D. in Robotics, Computer Science, Electrical Engineering, or related field
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience in dexterous manipulation, learned robotic policy deployment, or control theory applied to real hardware
• Experience designing data collection protocols and building high-quality ML datasets at scale
• History of mentoring engineers and influencing technical direction beyond your immediate team
• Deep familiarity with robotics frameworks (e.g., ROS/ROS2) and real-time robotic control systems
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

Pay

$183,997/year to $257,000/year + bonus + equity + benefits. Individual compensation is determined by skills, qualifications, experience, and location.